DataScience: Install tools for Scientific Data Processing

This article gives a brief overview of how to install some of the packages required for scientific data processing.

With focus on the python, we can start with the conda that provides with the complete environment to get all the required binary packages.

Step 1: Installing conda:

This will give you a scientific python environment and the "conda" command for installing other software. 

To install, go to:

http://www.continuum.io/downloads

and select the option appropriate for your system. Choose the Python 2.7 option (and not Python 3.x).

Step 2: Install NCL, PyNIO, PyNGL, and other tools

(Requires that step #1 be complete.)

First open a terminal window where you can type UNIX commands, and type:

conda create --name ncl_env --channel dbrown --channel khallock ncl pyngl pynio matplotlib basemap ipython jupyter

This will create a separate environment named ncl_env where the packages will be installed. Using a separate environment is a good idea because you don't mesh up with your existing environment and you can alter this environment as your requirement later.

The above command will install the ncl, pyngl, pynio, matplotlib, basemap, ipython, and jupyter in the ncl_env environment.

If you want to remove already existing environment (for instance,  "ncl_env"), then execute the following command:

conda env remove -n ncl_env 

You can then test with:

source activate ncl_env ## to activate the ncl_env environment 

ncl -V ; ng4ex xy01n -clean

python -c "from mpl_toolkits.basemap import Basemap"

You can verify the jupyter installation by just typing the following in the console:

jupyter notebook

Thanks.

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